Enabling Path of Digital Pathology to

Personalized Medicine

Session #74, February 12, 2019

Matthew G. Hanna, MD, Memorial Sloan Kettering Cancer Center

Rajendra Singh, MD, The Mount Sinai Hospital

Matthew Hanna, MD

Advisory Board, PathPresenter

Rajendra Singh, MD

Founder, PathPresenter

Conflict of Interest

Have no real or apparent conflicts of interest to report

Agenda

Intro

Ecosystem

Educational

Initiatives

Current

Landscape

end

Q/A

Digital

Pathology

PathPresenter

FUTURE

AI/ML

Personalized

medicine

Learning Objectives

Define what is digital pathology and what is its promise

Design an effective program that will train the pathologists of today and

tomorrow in digital pathology

Practice using digital pathology for educational, research, and clinical

purposes

Outline path of pathology to digital pathology to computational pathology

and finally to personalized medicine for patients

Film photography is

now a niche field

2001

E-book market jumpstarted in 2009.

Did not invest in digital solutions.

2011

Failed to identify digital

photography as a disruptive

technology, had to sell film,

patents, scanners to stay alive

2012

Failed to innovate a digital solution.

Netflix added streaming services in 2010.

2010

Years Companies Filed for Chapter 11

Life of Patients’ Specimens

Digital Pathology Basics

THE FIVE RIGHTs OF DIGITAL PATHOLOGY

RIGHT PATIENT

RIGHT SLIDE

RIGHT

PATHOLOGIST

RIGHT TIME

“Telepathology”

RIGHT

DIAGNOSIS

Digital Pathology Ecosystem

Resource: Hanna, M. G., & Pantanowitz, L. (2019). Digital Pathology. In R. Narayan

(Ed.), Encyclopedia of Biomedical Engineering, vol. 2, pp. 524–532. Elsevier.

Digital Pathology Subsystems

Software

Hardware

Whole slide image

Slide Scanner

Slide scanning

Robotics/slide handling

Optics/Lighting

Tissue detection

WSI viewer

File format

WSI acquisition

WSI repository

Compression

Image analysis

Digital Pathology Process

ARMS

Acquisition

Retrieval/Storage

Manipulation

Sharing

1x magnification

20x magnification

40x magnification

Digital Pathology Benefits

On-demand Archive/Case management

Glass slides storage

Move slides from local

To remote

↓ Costs

Archival glass slide requisitions had a 93% decrease in requests

47,387

186,607

424,901

19,369

20,745

12,336

1,426

5,000

10,000

15,000

20,000

25,000

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

2014 2015 2016 2017

Glass Slide Requests (n)

Digital Slides (n)

Digital slides available Glass slide requests

 Slide storage costs projected savings of $274,000/year

 Due to decreased vendor services

 (i.e. asset retrieval, storage proximity, labor)

Image Analysis

Wang, Khosla, … Beck (2016) https://arxiv.org/abs/1606.05718 Camelyon16 (JAMA, 2017)

Machine Learning

Big Data meets Pathology

Massive volume of digital data generated from WSI & bioinformatics/molecular data

Critical for personalized medicine, health systems, basic research and “Big data”

Dataset sizes: Computer vision vs. computational pathology

1 whole slide = 100 X 60,000 = 6 billion pixelsFrom Fuchs, 2017

Computational Pathology

Why is this possible now?

Image datasets

Cognitive

algorithms

Fast

computing/GPUs

Challenges

Not always being done with pathologist involvement, mostly being

done in computer science departments

No universal platform to aggregate and share the vast amount of

data generated by pathology across thousands of hospitals, medical

centers and reference laboratories

Available solutions are often scanner specific, lack useful

apps/tools for Pathologists, lack active participation of

pathologists and lack high quality aggregated data

You would feel comfortable providing primary diagnosis using

digital pathology, with retrieval of glass slides available upon

request

You would feel comfortable providing primary diagnosis using

digital pathology, without availability of glass slides

What can be accomplished?

• Education

– Trainee/faculty education/CME

• Clinical

– Create efficiencies for pathologists

• Research

– Identify digital prognostic markers

Education

Why is there a need?

Lack of open-access to digital slides or are

restricted by firewalls to download software

Learning from digital slides is not only having

access to digital slides; it should also simulate

current teaching techniques

CURRENT TEACHING TECHNIQUE

Outdated, Unscalable, Limited

http://www.teachingmicroscopes.com

Current landscape of Digital

Educational Resources

PathXL

DPA

CAP Case of the Month

PathXL

http://www.pathxl.com/pathology-education-tutor

PathPresenter

• Digital pathology company built by pathologists for pathologists

• Focused on building software to enhance and standardize the

learning and teaching experience in pathology

• Provide a multidisciplinary educational environment

Current PathPresenter Apps for education

• Developed Applications for Public or Institutional Use

MySlideBox

Manage your digital slides and

folders.

High Yield

Learn and study from hand-picked

cases to prepare for board

examinations, or to brush up on must-

know diagnoses

My Presentations

Create and manage your presentations

using our extensive Slide library or by

uploading your own slides

Quiz

Search, view, or share from thousands

of cases covering all medical

subspecialties

Slide Library

Search, view, or share from thousands

of cases covering all medical

subspecialties

Group Chat

Create group with other members and

discuss slides.

Analysis

Create Analysis and

collaborate to add

annotations and discussions

in Groups

Cross check the Quality of

Diagnosis by assigning to the

expert reviewers

MySlideBox

Slide Library

My Presentations

High Yield Sections

Quiz Module

Steps to Facilitate Education

•Provide an easy to use platform for trainees, faculty,

and pathology departments

•Provide high quality content

•Content validated by experts

•Publicized on social media

Path of Pathology to Personalized Medicine

Bring digital

pathology to

the world

Provide a new

standard medical

presentation

platform

Make

pathologist

comfortable

using digital

pathology

High quality

curated

digital

images

Pathology to

personalized

medicine

Growth in

pCAD

Use Cases

• Physicians

Ready access to a wealth of data and images, with seamless

medical presentations

• Institutions

Branded platforms with site specific content, monetized to the

medical community

• Pharma

Agnostic platform coupled with pathology data and AI apps for

real time analysis

LEARN, TEACH, CONSULT, RESEARCH, PUBLISH, CME

Is it really working?

• Usage by country/continent

>162

Countries

Users

>62,000

>10,000

Digital Images Apps

30%

Why this will only increase

Future

Pathologists

Number of

cancer cases

70%

How will AI affect Pathology

Education

De-skilling

Access to resources

Clinical & Research

Digital Pathology &

Personalized Medicine

Digital Pathology Slide

Cancer

registry

data

Clustering corresponded with molecular gene expressions and prognosis

Survival and Relapse

https://ai.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

https://ai.googleblog.com/2018/04/an-augmented-reality-microscope.html

Assistive screening tools for pathologists

Resource:

https://ai.googleblog.com/2018/04/an-augmented-reality-microscope.html

https://ai.googleblog.com/2018/10/applying-deep-learning-to-metastatic.html

LYNA (LYmph Node Assistant)

ARM

(Augmented Reality Microscope)

Novel Technologies: Multiplex

(h) autofluorescence

(i) Red = tumor

Green = stroma

(j) Double positivity

yellow = HER2+/Ki-

67+

blue = HER2–/Ki-67–

red = HER2–/Ki-67+

green = HER2+/Ki-67–

Multispectral Imaging. A Review of Its Technical Aspects and

Applications in Anatomic Pathology. J. R. Mansfield

HER2 PR Ki67 ER

Will AI/New tech Lead to Better Patient Care?

 Digital pathology is increasingly being used and will be a

key enabler of personalized medicine.

 Many areas of medicine including clinical, education, and

research are creating and utilizing digital imaging

applications including AI/machine learning.

 Pathologists’ current routines is transforming and being

impacted by digital pathology.

 We need to continue to partner with industry vendors and

continue to build applications of WSI for clinical use

including primary diagnosis and image analysis to help

drive personalized medicine.

Take Home Messages

The Road to Personalized Medicine

• Matthew G Hanna, MD

• mghannamd@gmail.com

• Rajendra Singh, MD

• skinpathology@gmail.com

• Please remember to complete online session evaluation

Questions